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How AI Marketing Works: Achieving 1-to-1 Personalization at Scale

Raj Balasundaram
Raj Balasundaram , Vice President of Solutions and Strategic Services

When you have experiences with brands that seem so tailored to you as an individual, have you ever wondered how they do it… or how you can too?

True 1-to-1 interactions today go beyond using your name. The brands that have really mastered personalization present enticing recommended items, reminder cart abandonment emails, and use unique codes and coupons per individual.

The best marketing today reads the thoughts of customers, and even foretells the future (okay, not literally, but you get the idea, right?). It helps customers by giving them exactly what they want and even offers predictions as to what they are likely to want next.

How can this all be done? Artificial intelligence marketing.

AI — today more of a buzzword than well-understood technology — is designed to optimize marketing tasks, tools, and outputs. It’s on the verge of transforming our roles and is serving as a catalyst to the evolution of e-commerce.

Global marketing organizations are using AI and its subset technologies — machine learning and deep learning — within their strategies to unify the entire customer experience with “that little extra.”

More than half of global marketers are using AI for personalization, to understand cross-channel customer behavior, and manage interactions. Source: Building Trust And Confidence: AI Marketing Readiness In Retail and eCommerce, Emarsys & forrester, June 2017

Throughout the rest of 2018 and into 2019, we’ll begin to see 1-to-1 marketing in action and pinpoint areas of influence, success, and improvement.

This brings up several interesting questions: what is true 1-to-1 marketing (what does it look and feel like), how does it actually work within a marketing platform (what’s actually happening beneath the hood), and how does AI play into all of this?

1-to-1 Marketing is Unique to the Individual

The beauty of AI is that it can define segments down to the individual — each person can get their own email, text message, app notification, web content, or overlay… virtually anything customizable can be customized.

In its simplest form, true 1-to-1 marketing means each person gets their own content, their own experience.

If you have 3 million contacts, for instance, but you have 1 million segments, that’s not 1-to-1.

1-to-1 marketing is even more granular, more relevant, and ideally more engaging than mass marketing or it’s sister, “segmentation.” 1-to-1 ensures individualized messages are made for every customer — though these terms of personalization, individualized, 1-to-1, customized, and more are often used interchangeably.

What does 1-to-1 marketing look like? Let’s look at a few examples.

Incentives

1-to-1 marketing brings an unmatched “human” touch. In that spirit, Sigma Beauty sends an individualized code to customers.

Image source: Sigma Beauty

Birthdays and other anniversaries

Many B2C brands already do some triggered communications around key dates for customers. These are a sort of “must” in e-commerce (and tactics you can’t afford to get wrong):

Image source: Sunglass Hut

Real-time availability

“Open time content” is a capability that enables you to provide real-time transparency into the status of fluid elements like availability — and use interesting touches like countdown clocks:

Image source: Carnival

Abandonment emails

You know the ones — you’re browsing an online store or begin to build a shopping cart, but exit your browser before completing a purchase… then, voilà! A couple hours later, you receive an email prompting you to resume your activity:

These examples scratch the surface of the potential of AI-infused marketing technologies. But they give you an idea of how the disruptive technology can manifest outwardly within your marketing.

The Problem of 1-to-1 Marketing

The problem is that 1-to-1 marketing is impossible to achieve manually. Marketers that attempt to achieve the above kinds of tactics manually may find some minimal and isolated success but ultimately become crazed and overworked — driving themselves mad, like elves frantically and furiously breaking their backs to create, wrap, and organize every Christmas gift without an assembly line to help mechanize the process.

When you want to achieve 1-to-1 marketing at scale across gigantic databases of hundreds of thousands of contacts, this requires specialized technology that can handle massive amounts of customer data and crank out intelligent outputs.

Using Tech to Help with 1-to-1 Marketing

The majority of modern-day marketing suites tend to enable some level of personalization/customization, but only on a channel-by-channel lens.

This siloed approach limits the capabilities, creativity potential, and visibility of marketing teams, and, most importantly, almost always causes a fragmented customer experience. To overcome this common technological limitation, these brands often find that communications work best when they’re calculated and executed based on singular customer events (defined, isolated instances like a customer making a purchase, or implicit events like customer churn and attrition).

The best 1-to-1, omnichannel experiences are built in engines that are channel-agnostic, ensuring every interaction is unique, containing the best content, independent of channel.

For example, a platform that consolidates all web, mobile, email and purchase information into a unified customer profile would include preferences, behavior trends, predicted behaviors, propensities, and affinities for individuals. This unified customer profile is the “single source of truth,” the foundation for which hyper-personalization can begin to take place across all channels.

Personalization engines understand the nature of individual events, and they can associate context with events, then choose relevant content (without any channel-specific styling), and ultimately syndicate that output via the preferred channel of the customer.

If this sounds far-fetched, complicated, or too techy, rest assured that it’s the only way by which true 1-to-1 is happening today. By working with the machine (in essence, AI, as we get to below) you VASTLY simplify this process — relying, as it is, on the genius of the machine to take over the pulling of the strings in your show. Now, you don’t have to understand the ins and outs of the machine for this stuff to work. But if you want to pull back the curtain just a tad, read on.

How Does Artificial Intelligence Marketing Actually Happen?

…and what is the machine really doing that’s so cool?

As mentioned, by working with an AI-enabled marketing automation system, you can automate the process of delivering 1-to-1 experiences to your entire database, at scale, across every channel. Let’s lift up the hood and see how it all happens.

Artificial intelligence works best when it’s weaved into the fabric of a marketing platform. This distinction is critical — AI isn’t one individual tool or thing. It’s a part of the entire system. In other words, AI isn’t an individual atom making up the body; it’s the emotion or love or air that runs throughout the body.

An underlying layer of code that’s hard-wired to “self-learn” can work with multiple channels, in multiple instances, and across a database. That means that AI works best when vertically integrated across a platform for enhanced capabilities, not when implemented within a single channel.

An embedded code lies underneath and informs every task that an AI-enabled marketing platform handles. While this illustration incorporates complex actions and confusing processes, it shows how AI is ingrained into an automation platform. Image source: Emarsys

Self-learning systems — which most AI-branded tools should also be — have to learn on their own, creating, reacting to, and defining rules that aren’t explicitly told to them by humans. On top of all that, these processes will all need to occur within a matter of milliseconds. A solution that helps you do this ostensibly sits atop all customer data with 360-degree coverage — including CRM, behavior, product, and external datasets.

The good news? AI-driven solutions are built to make this easy to manage so you’re as hands-off as possible — in fact, they work best this way.

The best AI machines literally let you tell them your strategy (e.g., setting a sliding scale to indicate how aggressively you want to discount an item for a particular campaign), and then do the rest.

AI systems lean on complicated algorithms (which, like the fire burning the coal, you don’t touch) that work in conjunction with previous behavior data to develop probabilities of certain events happening (like a customer purchasing), taking into account expected revenue/cost as well as the guidelines that you set in place to create a final output. The whole process works at once, kind of like this:

AI-enabled machines use algorithms, customer data, and other variables to help marketers send content most likely to drive action, at the best time, to every contact.

Through an extendable model, users can add many contact fields, relational data tables, or decision trees to create quite sophisticated models for campaigns.

Use case: 1-to-1 incentives  

Let’s look at one use case, and how it works: incentives.

AI-enabled engines typically contain rules for personalizing. So, during “send-time,” the channels basically dial up the personalization engine, and request content for individual contacts.

Since the machine is programmed to (a) consider all previous purchase, historical, and website data of each contact, (b) understand that information, (c) develop customized communications mostly likely to convert each contact, then (d) send, it can intelligently, automatically evaluate how much to discount for every customer:

Incentivization is unique to every person — some people require steeper discounts, while some require no incentive. The machine knows how much to take off for every customer to maximize likelihood of purchase.

Consumers are then provided with incentives most likely to engage them, personalized at the point of interaction.

Pro Tip: There’s a lot of fear and rhetoric about AI taking jobs. It won’t! Menial and repetitive tasks like segmenting data, crafting campaign blueprints, and creating if-then rules should be and can be offloaded to the machine. In addition to a superior customer experience, half of the point of using AI is to relieve your workload, and create efficiencies previously unattainable.

When all of this comes together, the end result is true omnichannel 1-to-1 marketing that is driven by AI. AI marketing is, indeed, the bridge that leads to scalable, individual interactions.

Final Thoughts

AI is real, and it allows us to solve real problems for real people — to help our customers, by:

  • Trying to anticipate what else they might find helpful in tandem with a current or recent purchase, e.g. via product recommendations
  • Allowing customers to stay up-to-date with content that populates in real-time based on when it’s opened, e.g. weather updates or local hotel availability
  • Making it easy to take the next best action in a given circumstance, e.g. with timely push notifications from a mobile app

As an optimization technology, and depending upon how much quality data you have and which technology you’re using, AI can help you deliver a mildly better to drastically enhanced customer experience.

Whether the marketing masses know it or not, AI has the potential to be the salvation that time-strapped, over-worked teams have been waiting for.

AI marketing solutions connect the entire marketing spectrum, including customer data, access to that data by the marketer and machine, campaigns and content, and execution. AI will help you provide 1-to-1 personalization for each and every one of your deserving customers. ◾

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About the Author


Raj Balasundaram is Vice President of Solutions and Strategic Services at Emarsys, where he helps leading brands leverage their digital platforms and data to out-maneuver competitors and achieve superior financial results. Raj has delivered presentations and talks at a variety of global conferences and road shows including #DMWF Expo Global, evangelizing the art of data intelligence based marketing. Prior to Emarsys, Raj worked at both Oracle and ExactTarget.

Connect with Raj: LinkedIn


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